Last week I attended VMWorld, the conference for VMWare customers and partners. I know what you are thinking: “why would a DataChick go to a conference about virtualization technologies?”

Yes, VMWare is a bit off my normal path of events and writings, but that makes it even more interesting to me. I attended because:

1. Tech Field Day Extra

Tech Field Day invited me to attend Tech Field Day Extra (#TFDx), which is an abbreviated version of their full events (like the Cloud Field Day 1 (#CFD1) I’m attending next week. Tech Field Days bring in vendor product teams to demo and talk about their products with independent professionals who share their thoughts about what they heard with their audiences and communities. I attended the presentations for:

Docker: Docker is software based on open standards that helps you package up all the parts of a solution and then deploy that anywhere. You may have heard people talking about containers and how they help with successful DevOps processes. By using containers, deployments are easier to deploy and scale. More about Docker.

I’ll be writing more about Docker and Datachick data pros in another post.

Primary Data: Primary Data presented about their solution Datasphere, a data virtualization product that uses some nifty market-optimization-like processing to automatically move data to where it needs to be, when it needs to be there. It’s “storage agnostic”, meaning through rules and group, data professionals can guide the right places for data to reside, and let the system decide (if needed), the fastest place for that data to rest.

I cover Primary Data in a future post, where I will talk about the use of rules and groups and objectives metadata to manage the data virtualization and data orchestration that are possible.

Sandisk: (owned now by Western Digital) Sandisk Data Center product teams talked with us about some deep dive internal virtualization features that frankly are well beyond my skills levels in virtual machines. As an overview, they talked about using Flashsoft for VMWare APIs for managing IO for storage / caches.

I will be hearing from again next week at Cloud Field Day 1, so I will be writing about them in a future post.

2. VMWorld Press

I was invited to VMWorld on a press credential. That meant I had access to all sessions and exhibits. I attended various press conference/meetings. I spent time talking to vendors who were most focused on data, DevOps and cloud technologies: Primary Data, SkyTap, SolarWinds, Datrium, Pure Storage, Dell Software, Turbonomic, X-IO, Github, Puppet, and SIOS. Most of my coverage of these technologies happened via Twitter @datachick. I expect from the conversations, though, that I will be covering these solutions and services in the longer term. Once this series is completed, I’ll wrap it up with some thoughts on VMWorld.

3. Professional Development

Over the last couple of years I’ve been focusing a lot of my professional development on cloud technologies and processes. This leads to learning more about hybrid technologies (cloud and on-prem, plus private clouds). All of this has shown me that I need to understand virtualization and data centre technologies more than I have had to know in the past. Working in other communities has helped me make the contacts and friends that I need to be successful. I think every few years IT pros should be an event that is related to but not the focus of their specialization to broaden their understand of the tiny piece of the puzzle they work on.

I also found some time to attend sessions and I hope to get some posts up later about the ones I picked.

4. My Own Data Management Environments

While I was attending these sessions and talking to vendors, I was thinking about the data tools environments I manage: repositories, model marts, data management tools, configuration files, etc. All of them can benefit from my implementing these technologies. It’s sort of a “metadata centre” I need to think about, too. I’m hoping to write about those experiences as well.

Finally

The advent of Software-defined {Storage | Data Centre |Networks | Software } means that configurations, metadata, policies, and rules will need to be well-managed. I see my job as a data professional just as applicable in managing data centre data as line of business data. If we aren’t apply our rules to our own work, then why would the business trust us when we tell them they should be doing that with “their” data?